Installation
The package is registered in the General
registry and so can be installed at the REPL with ] add StringDistances
.
Supported Distances
The available distances are:
 Edit Distances
 Jaro Distance
Jaro()
 Levenshtein Distance
Levenshtein()
 DamerauLevenshtein Distance
DamerauLevenshtein()
 RatcliffObershelp Distance
RatcliffObershelp()
 Jaro Distance
 Qgram distances compare the set of all substrings of length
q
in each string. QGram Distance
Qgram(q::Int)
 Cosine Distance
Cosine(q::Int)
 Jaccard Distance
Jaccard(q::Int)
 Overlap Distance
Overlap(q::Int)
 SorensenDice Distance
SorensenDice(q::Int)
 QGram Distance
 Distance "modifiers" that can be applied to any distance:
 Winkler diminishes the distance of strings with common prefixes. The Winkler adjustment was originally defined for the Jaro similarity score but it can be defined for any string distance.
 Partial returns the minimum distance between the shorter string and substrings of the longer string.
 TokenSort adjusts for differences in word orders by reording words alphabetically.
 TokenSet adjusts for differences in word orders and word numbers by comparing the intersection of two strings with each string.
 TokenMax combines scores using the base distance, the
Partial
,TokenSort
andTokenSet
modifiers, with penalty terms depending on string lengths. This is a good distance to match strings composed of multiple words, like addresses.TokenMax(Levenshtein())
corresponds to the distance defined in fuzzywuzzy
Basic Use
Evaluate
You can always compute a certain distance between two strings using the following syntax:
evaluate(dist, s1, s2)
dist(s1, s2)
For instance, with the Levenshtein
distance,
evaluate(Levenshtein(), "martha", "marhta")
Levenshtein()("martha", "marhta")
You can also compute a distance between two iterators:
evaluate(Levenshtein(), [1, 5, 6], [1, 6, 5])
2
Compare
The function compare
is defined as 1 minus the normalized distance between two strings. It always returns a Float64
between 0 and 1: a value of 0 means completely different and a value of 1 means completely similar.
evaluate(Levenshtein(), "martha", "martha")
#> 0
compare("martha", "martha", Levenshtein())
#> 1.0
Find

findmax
returns the value and index of the element initr
with the highest similarity score withs
. Its syntax is:findmax(s, itr, dist::StringDistance; min_score = 0.0)

findall
returns the indices of all elements initr
with a similarity score withs
higher than a minimum value (default to 0.8). Its syntax is:findall(s, itr, dist::StringDistance; min_score = 0.8)
The functions findmax
and findall
are particularly optimized for Levenshtein
and DamerauLevenshtein
distances (as well as their modifications via Partial
, TokenSort
, TokenSet
, or TokenMax
).
References
 The stringdist Package for Approximate String Matching Mark P.J. van der Loo
 fuzzywuzzy